Analyzing Big Data in Azure Cloud using Spark and Databricks
Databricks is one of the best tools for data exploration. It allows us to connect and query any data management service or read files in various formats. Databricks runs on every major public cloud, Azure, AWS, Google, and is tightly integrated with the cloud security, storage, and other cloud services. Databricks allows you to use the SQL language or programming languages like Scala or Python in a rich web interface based on Jupyter Notebooks.
During this session we will talk about Azure Databricks key features, and typical scenarios where Spark can fit, will see a lot of demos and I will share my top list of Azure Databricks best practices.
Maria has been working with data technologies for more than 20 years. She has extensive hands-on experience managing various data management technologies, including Postgresql, SQL Server, Azure CosmosDB, Azure SQL Database, Azure Synapse Analytics, Apache Spark, MySQL, AWS Aurora, Redis, AWS Redshift, Couchbase, and Elasticsearch, Snowflake, Google Big Query. She likes every aspect of data management, infrastructure, query tuning, monitoring, data analysis, and data visualization.
She is the main organizer of the Israel annual conference “DATA TLV” datatlv.com. Maria is one of the featured authors at mssqltips.com (mssqltips.com/sqlserverauthor/305/maria-zakourdaev)
|18u30||Welcome and introductions|
|18u30||Analyzing Big Data in Azure cloud using Spark and Databricks (75 minutes)|